Can I use this with Prometheus and Grafana?

Yes, the skill is designed to integrate with standard monitoring platforms like Prometheus and Grafana for advanced visualization and persistent alerting.

Does it support threshold-based alerting?

Absolutely; it helps you define specific error types and thresholds to trigger notifications via your preferred channels before issues impact your users.

What kind of errors can it track?

It tracks a wide range of errors including HTTP 4xx/5xx status codes, database connection failures, query timeouts, API response failures, and background task exceptions.

How does the Error Rate Monitor identify issues?

It analyzes logs and metrics from various sources like HTTP endpoints, database queries, and background jobs to identify patterns, exceptions, and threshold violations.

Error Rate Monitor

Name: Error Rate Monitor
Author: jeremylongshore

byjeremylongshore

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1,909

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分析与监控

Monitors and analyzes application error rates across HTTP endpoints, databases, and APIs to ensure system reliability and uptime.

The Error Rate Monitor skill automates the detection and analysis of application failures by tracking HTTP status codes, database exceptions, and background job timeouts. It enables developers to proactively identify reliability issues through threshold-based alerting and error budget tracking, helping teams maintain high service-level objectives (SLOs). Whether setting up monitoring for a new service or diagnosing recurring patterns in legacy logs, this skill provides actionable insights and visualization strategies to minimize downtime and improve overall system health.

主要功能

01Granular log analysis and failure pattern detection

021,909 GitHub stars

03Automated error source identification for HTTP, DB, and API layers

04Error budget tracking and SLO/SLI alignment

05Dashboard and visualization configuration for error metrics

06Threshold-based alerting and notification channel configuration

使用场景

01Setting up real-time error monitoring for a new production web application

02Diagnosing the root cause of frequent background job failures or timeouts

03Establishing error budgets and reliability targets for legacy systems

主要功能

01Granular log analysis and failure pattern detection

021,909 GitHub stars

03Automated error source identification for HTTP, DB, and API layers

04Error budget tracking and SLO/SLI alignment

05Dashboard and visualization configuration for error metrics

06Threshold-based alerting and notification channel configuration

使用场景

01Setting up real-time error monitoring for a new production web application

02Diagnosing the root cause of frequent background job failures or timeouts

03Establishing error budgets and reliability targets for legacy systems